Your SlideShare is downloading. ×
0
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
ICIC 2013 New Product Introductions Averbis
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

ICIC 2013 New Product Introductions Averbis

471

Published on

Published in: Technology, Education
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
471
On Slideshare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
11
Comments
0
Likes
1
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Averbis Patent Analytics Dr. Katrin Tomanek
  • 2. ABOUT AVERBIS Founded in: 2007 Headquarter: Freiburg im Breisgau, Germany Team: Domain- & IT experts Focus: Leverage structured & unstructured information Current Sectors: Pharma, Health, Automotive, Publishers & Libraries
  • 3. SELECTED CUSTOMERS
  • 4. CHALLENGE Patent applications: Exponential growth of data • need for data-driven decisions • limited human resources for analysis Medline articles: New analytics tools needed for • Semantic search and discovery • Competitor analysis • Identification of market trends • IP landscaping • Portfolio analysis • …
  • 5. OUR PORTFOLIO
  • 6. MAIN FEATURES Information Extraction A learning system Powerful frontend
  • 7. INFORMATION EXTRACTION Linguistics • Segmentation • Syntax • Negation • Speculative language • … Entities & Relations • Diseases, Targets, Chemicals • Indications ↔ Targets • ….
  • 8. A LEARNING SYSTEM
  • 9. FRONTEND
  • 10. NOT ONLY FOR PATENTS
  • 11. THOUGTHS? For more information, please contact Dr. Katrin Tomanek katrin.tomanek@averbis.com +49 761 - 203 9769 0

×